Evidence map›Paper›PMID 42046509›Full record

ReviewJournal of microbiology and biotechnology2026

Chemicals Affecting Autophagy in rCHO Cell Cultures and Their Impacts on Therapeutic Protein Production Processes.

Hoon-Min Lee, Yeon-Gu Kim

Abstract readReview
In one paragraph

Review in Journal of microbiology and biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Hoon-Min LeeBiotherapeutics Translational Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 34141, Republic of Korea.
Yeon-Gu KimBiotherapeutics Translational Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 34141, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autophagy is a cellular process that is essential for maintaining homeostasis in mammalian cells by degrading and recycling intracellular components, particularly under stress conditions. To achieve high therapeutic protein production in recombinant Chinese hamster ovary (rCHO) cells, it is necessary to develop a fed-batch culture process using optimized culture media that maintains a rapid growth rate and extends the culture longevity of cell lines with high specific protein productivity. During the development of these culture processes, stressful conditions, such as rapid nutrient deprivation and hyperosmolarity, which may occur through the repeated addition of nutrient concentrates, can induce autophagy in rCHO cells. Proper modulation of autophagy promotes cell survival by alleviating cellular stress rather than promoting cell death, thereby improving cell viability and therapeutic protein production in rCHO cell-based processes. This review discusses the various chemicals known to inhibit or induce autophagy in rCHO cell cultures, their mechanisms of action, and their effects on the production efficiency of therapeutic proteins. Understanding these mechanisms provides insight into improving the productivity and quality of therapeutic proteins during rCHO cell-based bioprocesses.

Indexed as

AutophagyRecombinant ProteinsAnimalsBatch Cell Culture TechniquesCell Culture TechniquesCell SurvivalCHO CellsCricetinaeCricetulusCulture MediaCulture MediaRecombinant ProteinsAutophagy-inducing chemicalsAutophagy-inhibiting chemicalsProtein productivityRecombinant CHO cell cultureTherapeutic protein production

Identifiers

PMID42046509
PMCPMC13128665

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.